INCREASING GEOMETRIC ACCURACY OF DMC’S VIRTUAL IMAGES

In the last two to three years, there have been a number of investigations into the geometric accuracy of large format digital cameras, particularly for large scale and engineering application. Geometric calibration of a silicon pizza image from a multi-camera platform seems to be the most challenging issue. The main problems in this effort include a combined camera lens and imaging raster frame calibration at the same time and a multi-camera platform exterior orientation (EO) calibration. Not corrected systematic image errors reduce the image accuracy and can propagate unfavorably into object space during aerial triangulation. This leads to a lower vertical accuracy of determined object points. In this paper, two different methods are used to remove or model the remaining systematic errors of the DMC (Intergraph Digital Mapping Camera) virtual images: the first method tries to remove systematic image errors by a posteriori interpolation treatment of the image residuals from bundle adjustments of test field blocks. Correction grids are then used as inputs in the DMC Post-processing software to generate virtual images or used in the real-time math model of the ImageStation products. The second method tries to describe the systematic errors using “proper ” sets of additional parameters in self-calibration bundle adjustments. These methods were applied on the several DMC test blocks of varying GSDs (Ground Sampling Distances). This study showed that the magnitude of the remaining systematic errors of the image residuals is constant and ranges between 0.5μm and 3μm. Furthermore, these methods were able to increase the vertical accuracy of the object points by a factor 2 to 4 times